Develop a Risk Prediction Model for Phthalate-ester-induced Diseases

Completed

• Conditions: Plasticizers

• Registration Number: NCT05892029
• Lead Sponsor: National Taipei University of Nursing and Health Sciences

Brief Summary

This exploratory study collected basic demographic and laboratory data from the Taiwan Biobank using artificial intelligence algorithms and applied data mining to identify the correlations between phthalate esters \[di(2-ethylhexyl) phthalate, DEHP\], lifestyle, and disease.

Detailed Description

This study was designed as exploratory research. The Institutional Review Board and the Taiwan Biobank approved the study before it was conducted (Approval Number: TWBR11007-06). The data set included information from participants between 30 and 70 years old who were tested for PAEs between 2016 and 2022 (1337 cases). The data set includes (1) questionnaire responses, such as basic personal information, individual health behaviors, and female health issues; (2) physical examination results, such as body mass index (BMI), body fat percentage, waist circumference, hip circumference, waist-to-hip ratio, blood pressure, heart rate, pulmonary function, and bone mineral density; (3) blood and urine analyses results from blood tests, serology tests, hepatobiliary function tests, renal function tests, and urinalysis; and (4) data on PAE content of urine

Study Timeline

• Study Start: 2021-01-01
• Primary Completion: 2022-12-31
• Study Completion: 2022-12-31
• Status Verified: 2023-05
• Study First Submitted: 2023-05-19
• Study First Submitted QC: 2023-05-26
• Last Update Submitted: 2023-05-26
• Study First Posted: 2023-06-07
• Last Update Posted: 2023-06-07

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 1136

Inclusion Criteria

Not provided

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Exclusion Criteria

Not provided

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Risk assessment analysis of disease and PAEs	2022	(1) questionnaire responses, such as basic personal information, individual health behaviors, and female health issues; (2) physical examination results, such as body mass index (BMI), body fat percentage, waist circumference, hip circumference, waist-to-hip ratio, blood pressure, heart rate, pulmonary function, and bone mineral density; (3) blood and urine analyses results from blood tests, serology tests, hepatobiliary function tests, renal function tests, and urinalysis; and (4) data on PAE content of urine.
Artificial intelligence prediction model for diseases and PAEs	2022	to apply machine learning to establish the correlations between the environmental hormone PAE and high disease risk and suggest assessment items for nursing intervention.

Trial Locations

Locations (2)

Cheng Hsin General Hospital; 🇨🇳 Taipei, Taiwan

National Taipei university of nursing and health science; 🇨🇳 Taipei, Taiwan